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Expansion of the measurement database and validation of the algorithm forecasting the impact of traffic-induced vibrations on residential buildings
Traffic-induced vibrations can be a heavy operational load on a building, causing cracks in plaster, scratches in the structure, cracking of structural elements or even the collapse of the structure. Vibration measurements on real objects are laborious and costly, and what is important, they are not justified in every case. It is important to find systems that predict the impact of vibrations on residential buildings that are both useful and inexpensive. There are many methods used to predict various types of adverse phenomena in civil engineering, starting from decision trees, risk analysis, through statistics and random algorithms, to artificial intelligence and machine learning. An example here are artificial neural networks (ANN) and algorithms based on support vector machines (SVM). Therefore, the aim of the research is to create an original system based on this type of methodology, thanks to which the risk of negative dynamic impact on a given residential building can be predicted with a sufficiently high probability.
Objectives:
1. Database expansion
• Conducting own research:
• Obtaining research results
2. Analysis of new cases
3. Increasing the publication
Details
- Financial Program Name:
- MINIATURA
- Organization:
- Narodowe Centrum Nauki (NCN) (National Science Centre)
- Realisation period:
- unknown - unknown
- Project manager:
- dr inż. Anna Jakubczyk-Gałczyńska
- Realised in:
- Department of Building Engineering
- Request type:
- National Research Programmes
- Domestic:
- Domestic project
- Verified by:
- Gdańsk University of Technology
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